This is a "map" visualization, meaning that the images are plotted in a coordinate space — here, a 2D t-SNE embedding of a 5-dimensional "histogram space", derived from Google's Cloud Vision API. When you make a tag request for an image, Google returns a list of tags, each with a confidence score. The higher the score, the surer Google's classifiers are that the tag applies to the image. The plot here uses as its plot elements (and its feature space) something I call a "histogram line": a line that connects the tops of histogram columns, to simplify its visual representation. These are fairly simple 5-bin histograms, each bin representing a range of possible tag scores (they range from 0.5 to 1). These 5-dimensional vectors sit, therefore, in a 5-dimensional similarity space. The map here groups together tags that have similar confidence profiles.